# Comparing the effectiveness of ring and block-vaccination strategies on networks

## TL;DR

The paper compares ring and block-vaccination strategies on networks to control disease spread, finding that timing and strategy affect their effectiveness.

## Contribution

The study introduces a family of ring vaccination-inspired strategies and evaluates their performance in preventive and containment scenarios on synthetic and real-world networks.

## Key findings

- In preventive scenarios, ring vaccination outperforms block vaccination by reducing epidemic size or even preventing outbreaks.
- In containment scenarios, both strategies perform similarly but block vaccination uses fewer resources.
- The models were applied to a real-world case of Xylella fastidiosa in olive trees in Italy.

## Abstract

Vaccination is vital for preventing disease spread, as demonstrated by its role played in recent outbreaks such as measles, COVID-19, and the 2014 West Africa Ebola crisis. Classical ring vaccination–targeting individuals near infected cases to form protective clusters–has become of interest due to its effectiveness, yet it is strongly influenced by the quality of contact tracing and availability of medical resources. Here, we model the efficiency of a family of ring vaccination-inspired strategies that address these limiting factors and disentangle them from the structure of the contact patterns. In particular, we evaluate scenarios that consider a vaccination radius r, used to vaccinate nodes in the network up to r contacts away (block vaccination) or exactly r contacts away (ring vaccination) from nodes of interest. Each one of these is tested under two further scenarios: the preventive one, where individuals are vaccinated before the epidemic takes place, and the containment one, where vaccination occurs during an outbreak to limit disease spread. They are tested in synthetic networks, where we find that in the preventive scenario, ring outperforms block vaccination, reducing the size of the epidemic and, in some cases, even preventing it from happening. On the other hand, in the containment scenario, we find that both strategies perform slightly similarly in reducing the impact of the diseases but block vaccination using fewer resources. As a case study, the proposed strategies are used to create epidemiological risk maps by employing the spatial position of olive trees in the Salento region in Italy, which recently suffered the impact of the bacterium Xylella fastidiosa.

Infectious diseases such as measles and Ebola have shown how quickly outbreaks can spread and how essential vaccination is to protect individuals. In our work, we investigate a spectrum of vaccination strategies, inspired by ring vaccination, that can help to contain the spread of epidemics by targeting individuals in close contact with confirmed cases. We explore two scenarios: a preventive scenario, where vaccines are administered before an outbreak begins, and a containment scenario, where vaccines are used to mitigate the spread of a disease that is already underway. We develop mathematical frameworks to describe the proposed models, utilizing synthetic complex networks as a proxy to mimic social contact patterns. We found that, depending on timing and strategy, these targeted approaches can be very effective, even stopping outbreaks entirely or reducing their impact while using fewer vaccine resources. To illustrate the performance and impact in a real-world setting, we framed our models within the context of olive trees in southern Italy, where a harmful bacterium has been spreading over the last decade. Our results suggest that such vaccination models could provide tools to prevent and face epidemic diffusion in a wide range of scenarios, from public health to agricultural decisions.